code: def decode(self, encoded_values_tensor):
      vec = []
      for encoded in encoded_values_tensor:
          decoded = self._tokenizer.decode(encoded)
          decoded = (
              decoded.split("[PAD]")[0]
              .rstrip()
              .lstrip()
              .lstrip("[CLS] ")
              .rstrip(" [SEP]")
          )
          vec.append(decoded)
      return vec
  
file_path: lightwood/lightwood/encoder/text/vocab.py
imports: import os
  import torch
  from transformers import DistilBertTokenizer
  from lightwood.encoder.base import BaseEncoder
label_desc: Use image node_id 4 for calling the VocabularyEncoder obj's underlying member method code with example usage: obj.decode(encoded_values_tensor) and returns: vec